We train the GATA through reinforcement learning, the experiment setting is same with Sec. REF .
Instead of initializing the word embedding, node embedding and edge embedding with fastText word vectors [1]}, we found that the action prediction task (AP), which is also included in GATA's work [2]}, could provide better initialization.
In light of this, we could like to conduct such task, and apply the AP initialization to all encoders (observation encoder, task encoder, action encoder).
Fig. REF  shows the action predicting process. Given the transition data, the task is to predict the action \(a_t \in \mathcal {A}\)  given the current observation \(o_t\) , and the next observation \(o_{t+1}\)  after executing \(a_t\) .
The transition data for AP task is collected from the FTWP game set and is provided by GATA's released code.
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